This section provides background information related to the present disclosure which is not necessarily prior art.
Photoacoustic imaging (PAI) technology, one of the most rapidly growing areas in medical imaging in the last decade, shows great potential for improved diagnosis, monitoring, and treatment of many diseases. Relying on the detection of ultrasonic signals generated by laser illumination on biological samples, PAI is able to achieve high-resolution in optically scattering biologic tissues at relatively large depths. The majority of previous studies on PAI are focused on total signal magnitudes as an indication of macroscopic optical absorption by specific chemical components at single or multiple optical wavelengths. However, because of the limited bandwidth in photoacoustic (PA) signal detection, and the uncertainty of light fluence in tissue, conventional PAI images remain largely qualitative. Moreover, PAI findings are highly dependent on the individual system and operator, and hence, are difficult to be reproduced and used for purposes of objective comparison.
The extensive study on frequency domain analysis of radio frequency (RF) ultrasound (US) signals, e.g., US spectrum analysis (USSA) as a quantitative US technology, has shown potential for evaluating several parameters (such as dimension and density) of microscopic backscatters in biologic tissues. USSA has been explored for many years for its capability to detect and characterize diseases, including non-alcoholic fatty liver disease (NAFLD). USSA, however, is a purely “physical” imaging technique due to its mono-physics nature. Evaluating physical parameters of microscopic backscatters in tissue without interrogating the molecular components or chemical substances forming these backscattering micro-features has limited not only its specificity, but also its sensitivity for diagnosis. For example, a change in US backscattering in liver may not be a result of fat accumulation in liver cells, but instead due to the large amount of collagenous fiber depositing in the extra-cellular spaces, e.g., liver fibrosis. It has also been reported that US cannot be reliably used for early detection, because US is less sensitive to mild fatty liver and cannot detect NAFLD reliably until the degree of steatosis is above 33%.
Due to the physical-limiting nature of PAI and the chemical-limiting nature of USSA, there remains a need to develop an imaging system that can analyze both physical and chemical biological structures simultaneously.